Ridge Regression achieved the best predictive performance, producing a slightly lower RMSE than Linear Regression.
Key predictors driving sale prices include square footage (Gr Liv Area), overall functionality (Functional_Sal), and squared living area, all showing strong, interpretable influence in the coefficient importance chart.
The Learning Curve indicates stable model behavior: Training RMSE decreases quickly with additional data, while validation RMSE levels off, suggesting the model is neither overfitting nor underfitting and benefits moderately from larger sample sizes.
Predicted vs. Actual values follow the 45-degree line closely, showing strong generalization and low systematic error.
Residuals are tightly centered around zero with limited spread, indicating minimal bias and well-distributed model errors.